Wireless Photoplethysmography Sensor for Continuous Blood Pressure Biosignal Shape Acquisition

Abstract

Blood pressure assessment plays a vital role in day-to-day clinical diagnosis procedures as well as personal monitoring. Thus, blood pressure monitoring devices must afford convenience and be easy to use with no side effects on the user. This paper presents a compact, economical, power-efficient, and convenient wireless plethysmography sensor for real-time blood pressure biosignal monitoring. The proposed sensor facilitates blood pressure signal shape sensing, signal conditioning, and data conversion as well as its wireless transmission to a monitoring terminal. Received data can, subsequently, be compiled and stored on a computer via a Wi-Fi module. During monitoring, users can observe blood pressure signals being processed and displayed on the graphical user interface (GUI)—developed using a virtual instrumentation (VI) application. The proposed device comprises a finger clip optical pulse sensor, analogue signal preprocessing, microcontroller, and Wi-Fi module. It consumes approximately 500 mW power when operating in the active mode and synthesized using commercial off-the-shelf (COTS) components. Experimental results reveal that the proposed device is reliable and facilitates efficient blood pressure monitoring. The proposed wireless photoplethysmographic (PPG) sensor is a preliminary (or first) version of the intended device manifestation. It provides raw blood pressure data for further classification. Additionally, the collected data concerning the blood pressure wave shape can be easily analysed for use in other biosignal observations, interpretations, and investigations. The design approach also allows the device to be built into a wearable system for further research purposes.

Measuring Biosignals with Single Circuit Boards

“…Arami et al, e.g., investigated the possibility to use Hall elements to measure knee flexion-extension in a smart knee prosthesis [ 159 ]. Blood pressure was continuously measured by Kuncoro et al, using an LED/photodetector system as a photoplethysmograph and an Arduino Beetle board for evaluation of the optical data, giving pulse and blood pressure [ 160 ].…”

Transformative Approach for Heart Rate Prediction from Face Videos Using Local and Global Multi-Head Self-Attention

“…With the introduction of digital cameras, remote heart rate monitoring has become accessible across diverse fields, encompassing hospital care [2], telemedicine [3,4], fitness assessment [5,6], motion recognition [7], and the automotive industry [8,9]. This remote method has extended its applications to numerous areas including mental stress detection, cardiovascular function variations, sleep quality assessment, and drowsiness identification [10][11][12].…”

Intelligent Remote Photoplethysmography-Based Methods for Heart Rate Estimation from Face Videos: A Survey

“…It can predict not only the heart rate but also other vital information, such as heart rate variability and blood pressure. thereby inferring mental stress [4], variations in cardiovascular functions, quality of sleep [5], and drowsiness [6]. The advent of the digital camera brought this remote method to the masses.…”